Multilingual knowledge base completion by cross-lingual semantic relation inference

• Autorzy: Bebeshina-Clairet Nadia , Lafourcade Mathieu

Identyfikatory

DOI

10.15439/2019F267

• Konferencja: Federated Conference on Computer Science and Information Systems (14 ; 01-04.09.2019 ; Leipzig, Germany)
• Języki publikacji: EN

Abstrakty

EN

Highly structured knowledge bases such as lexical semantic networks contain various connectivity patterns that can be learned as node features using dedicated frameworks. However, semantic relations are often unequally distributed over such knowledge resources. Some of the language partitions may benefit from integrating structured resources which are more easily available for resource-rich languages. In the present paper, we propose a simple endogenous method for enhancing a multilingual knowledge base through the cross-lingual semantic relation inference. It can be run on multilingual resources prior to semantic representation learning. Multilingual knowledge bases may integrate preexisting structured resources available for resource-rich languages. We aim at performing cross-lingual inference on them to improve the low resource language by creating semantic relationships.

Słowa kluczowe

EN

inference mechanism; knowledge based systems; artificial intelligence; natural language processing; semantic network

PL

mechanizm wnioskowania; systemy oparte na wiedzy; sztuczna inteligencja; przetwarzanie języka naturalnego; sieć semantyczna

• Wydawca: Polskie Towarzystwo Informatyczne
• Czasopismo: Annals of Computer Science and Information Systems
• Rocznik: 2019
• Tom: Vol. 18
• Strony: 249--253
• Opis fizyczny: Bibliogr. 25 poz., tab., wz., rys.

Twórcy

autor

Bebeshina-Clairet Nadia

• LIRMM, University of Montpellier, 860 rue de St Priest 34095 Montpellier, France

autor

Lafourcade Mathieu

• LIRMM, University of Montpellier, 860 rue de St Priest 34095 Montpellier, France

Bibliografia

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Uwagi

1. Track 2: Computer Science & Systems

2. Technical Session: 4th International Workshop on Language Technologies and Applications

3. Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).